How to implement QuickSort in Python


QuickSort is an in-place sorting algorithm with worst-case time complexity of n2n^{2}.


QuickSort can be implemented both iteratively and recursively. We’ll mainly focus on the recursive implementation, as it is far more convenient, intuitive, and simplistic – iterative implementation is generally unrecommended. Arrays are used as an example here, but QuickSort can be implemented on other data structures (like linked lists) as well.

The algorithm can be broken down into three parts​​:

  1. Partitioning the array about the pivot.
  2. Passing the smaller arrays to the recursive calls.
  3. Joining the sorted arrays that are returned from the recursive call and the pivot.

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In the above illustration, we used the first element of the array as a pivot, even though any of the elements could​ be taken​.


def QuickSort(arr):

    elements = len(arr)
    #Base case
    if elements < 2:
        return arr
    current_position = 0 #Position of the partitioning element

    for i in range(1, elements): #Partitioning loop
         if arr[i] <= arr[0]:
              current_position += 1
              temp = arr[i]
              arr[i] = arr[current_position]
              arr[current_position] = temp

    temp = arr[0]
    arr[0] = arr[current_position] 
    arr[current_position] = temp #Brings pivot to it's appropriate position
    left = QuickSort(arr[0:current_position]) #Sorts the elements to the left of pivot
    right = QuickSort(arr[current_position+1:elements]) #sorts the elements to the right of pivot

    arr = left + [arr[current_position]] + right #Merging everything together
    return arr

array_to_be_sorted = [4,2,7,3,1,6]
print("Original Array: ",array_to_be_sorted)
print("Sorted Array: ",QuickSort(array_to_be_sorted))